Amirkabir University of Technology Amirkabir Journal of Mechanical Engineering 2008-6032 54 2 2022 04 21 Lane Change Path Planning in Emergency Situation Based on Skilled Driver's Performance Lane Change Path Planning in Emergency Situation Based on Skilled Driver's Performance 269 288 4601 10.22060/mej.2021.20198.7191 FA Samir Neisy Minaee PhD Student, Department of Mechanical Engineering, Advanced Vehicle Control System Laboratory (avcs-lab), Faculty of Mechanical Engineering, K.N. Toosi University of Ttechnology, Tehran, Iran, Ali Ghaffari Professor, Department of Mechanical Engineering, Advanced Vehicle Control System Laboratory (avcs-lab), Faculty of Mechanical Engineering, K.N. Toosi University of Technology, Tehran, Iran, Journal Article 2021 06 23 Lane Change at high speeds is a strategic maneuver to avoid the collision. In this situation, The time of an accident possibility is mainly less than two seconds. therefore, finding the proper trajectory and control of the vehicle is crucial at the lowest cost. In this paper, based on a skilled driver’s performance in a similar situation, a proper path and corresponding appropriate control system was designed aiming at vehicle stability preserving and collision avoidance. To this purpose, possible paths were simulated and identified using the vehicle's seven degrees of freedom model and applying the driver’s behavior. A neural network system was trained; then, the trajectory was chosen. A hybrid controller was hired for the vehicle navigation, consisting of the driver's performance pattern with a covering neural network and two proportional derivative controllers. The Novelties of this method are the simultaneous design of a stable path while maintaining geometric constraints and the low computational burden of the path planning and control system. The results show that the highest neural network error is about 11%. Also, the control system has been able to steer the vehicle and follow the trajectory with 40cm maximum lateral displacement error in the speed and road friction different conditions. Lane Change at high speeds is a strategic maneuver to avoid the collision. In this situation, The time of an accident possibility is mainly less than two seconds. therefore, finding the proper trajectory and control of the vehicle is crucial at the lowest cost. In this paper, based on a skilled driver’s performance in a similar situation, a proper path and corresponding appropriate control system was designed aiming at vehicle stability preserving and collision avoidance. To this purpose, possible paths were simulated and identified using the vehicle's seven degrees of freedom model and applying the driver’s behavior. A neural network system was trained; then, the trajectory was chosen. A hybrid controller was hired for the vehicle navigation, consisting of the driver's performance pattern with a covering neural network and two proportional derivative controllers. The Novelties of this method are the simultaneous design of a stable path while maintaining geometric constraints and the low computational burden of the path planning and control system. The results show that the highest neural network error is about 11%. Also, the control system has been able to steer the vehicle and follow the trajectory with 40cm maximum lateral displacement error in the speed and road friction different conditions. https://mej.aut.ac.ir/article_4601_2f7e6adf17656e3c83056ca9b6dcb8b7.pdf